The way technology is shaping our lives – #WrapUp Nº 12

Why 500 Million People in China Are Talking to This AI

When Gang Xu, a 46-year-old Beijing resident, needs to communicate with his Canadian tenant about rent payments or electricity bills, he opens an app called iFlytek Input in his smartphone and taps an icon that looks like a microphone, and then begins talking. The software turns his Chinese verbal messages into English text messages, and sends them to the Canadian tenant. It also translates the tenant’s English text messages into Chinese ones, creating a seamless cycle of bilingual conversation.

In China, over 500 million people use iFlytek Input to overcome obstacles in communication such as the one Xu faces. Some also use it to send text messages through voice commands while driving, or to communicate with a speaker of another Chinese dialect. The app was developed by iFlytek, a Chinese AI company that applies deep learning in a range of fields such as speech recognition, natural-language processing, machine translation, and data mining

The automated city: do we still need humans to run public services?

Scientific advances and new technologies often enable dramatic improvements in public services and urban life, eradicating some jobs while creating new types of employment. But the next chapter of urban automation might be more profound than any previous one. In fact, it’s already begun.

“Smart cities” offer a seductive vision of a world where everything runs as smoothly as the latest iPhone. Need a parking space? An app will tell you where one’s available, and notify you (and your friendly neighbourhood parking inspector) when your time is up. It’s the kind of technology many cities are trialling, embedding sensors in streetlights, curbs and buildings to monitor parking, traffic and air pollution – even crime.

A New Mobile Chip Beams Data for Miles Using Almost No Power

For under a dime and with just a whisker of electricity, devices could send data throughout a building. Researchers at the University of Washington led by Shyam Gollakota, one of our 35 Innovators Under 35 in 2014, have built a new chip that uses reflected radio signals to efficiently transmit data over great distances.

The chip uses a technique called long-range backscatter to communicate with other devices. Instead of creating signals from scratch, it is able to selectively reflect radio waves that are already passing through space to create a new signal. The researchers built out several prototype devices that use the technology, including a skin patch and a connected contact lens like the one shown off by Gollakota at EmTech MIT in 2016, and tested them to find out how well they perform.

Drones and Robots Are Taking Over Industrial Inspection

Avitas Systems, a GE subsidiary based in Boston, is now using drones and robots to automate the inspection of infrastructure such as pipelines, power lines, and transportation systems. The company is using off-the-shelf machine-learning technology from Nvidia (50 Smartest Companies 2017) to guide the checkups, and to automatically identify anomalies in the data collected.

The effort shows how low-cost drones and robotic systems combined with rapid advances in machine learning are making it possible to automate whole sectors of low-skill work. While there is plenty of worry about the automation of jobs in manufacturing and offices, routine security and safety inspections may be one of the first big areas to be undermined by advances in Artificial Intelligence.

Does Your Genome Predict Your Face? Not Quite Yet

On Monday, the California gene-hunting company Human Longevity published a paper making the bold claim that it can identify individuals using their genomes to predict what their faces looks like. The assertion—that your DNA can be used to create a photo-like reconstruction of you—has potentially big implications. It would allow police to pick suspects out of a lineup using a blood spot and it would mean no genome collected for research is truly private.

But a withering reaction to the face-prediction paper by scientists on social media is probably not what Human Longevity’s founder, the famed genomics expert J. Craig Venter, had in mind. According to two experts who reviewed the paper—and one former employee—Venter can’t actually pick a person out of a crowd using a genome, and his report had difficulty finding a publisher. “Craig Venter cannot predict faces,” Yaniv Erlich, the chief scientific officer of MyHeritage.com, a genealogy website, said bluntly on Twitter. lution.